Conventional methods for assessing stimulus-evoked or event-related responses in biologic systems emphasize averaging responses to stimuli or events repeated at constant frequencies. In the case of the nervous system, for example, neurons generate electrical signals after stimulation of peripheral nerves, such as in the retina, the cochlea, or skin receptors. Recorded from the body surface, neurophysiological responses are as small as 10 microvolts (.mu.V) compared to background electrical noise which may be 100 .mu.V or greater. To resolve signal from noise, it is often necessary to average multiple responses in the time domain. Signal averaging is based on the principle that all electrical potentials that are not time-locked to the stimuli will tend to cancel while electrical responses time-locked to the stimuli will not. To obtain multiple responses for averaging, stimuli are usually delivered as a constant frequency train of pulses at high intensities to evoke the maximum response.
One disadvantage of conventional averaging methods is that they evaluate responses to only one stimulation frequency at a time. Examining responses evoked by only one stimulation frequency may yield misleading results. For example, low frequency stimulation may produce responses suggesting apparent normality even when the system is unable to respond to higher frequency stimulations which it can normally follow. On the other hand, the system may show diminished or absent responses at a higher stimulation frequency when it is able to follow slower stimulation. These situations probably account for a majority of false negatives and false positive test results of conventional averaged evoked response tests. Although the tests can be repeated at different stimulus frequencies, most excitable systems change during repeated prolonged high frequency stimulation. The averaging process itself obscures much information contained in the individual responses. The amplitudes and latencies of averaged waveforms do not necessarily represent either the averaged amplitudes or the average latencies of the individual responses. Nor can they show trends of responses during the stimulation. These are well known and recognized limitations of conventional signal averaging methods.
Another disadvantage of conventional averaging methods is their inability to assess stimulus thresholds, especially when response amplitudes are small relative to background noise. Due to limitations of resolving signal from noise, responses resulting from lower intensity stimuli may not be detectable. Conventional evoked response methods therefore usually rely on supramaximal stimulation, i.e., using stimulus intensities beyond which there is no further increase in response amplitude with greater stimulus intensity. This inability is a serious limitation. For example, most electrophysiological tests of hearing, visual, or other sensory functions require that patients give a subjective response as to whether or not they perceive a given stimulus in order to determine stimulus threshold. Such tests would be greatly enhanced by the addition of objective means of quantifying thresholds to low-level stimuli.
A further disadvantage of conventional averaging methods is their inability to detect or quantify certain intrinsic behaviors of excitable tissues. Repeated and prolonged high frequency stimulation, as indicated above, produce response fatigue. Fatigue is when responses decrease in amplitude and increase in latency with repeated stimuli; latency is the period of time between the stimulus and the response. Excitable biological systems often exhibit distinctive post-response characteristic called "refractory period" and "supernormal period". Refractory period is the time interval after a first response during which the tissue fails to respond fully to a second stimulus and manifests in decreased amplitudes and increased latencies. Supernormal period is the time interval after a first response during which the tissue is more excited by subsequent stimuli, manifesting in increased amplitudes and decreased latencies of responses. All three phenomena may occur with repeated stimuli. Not only are conventional averaging methods unable to distinguish between these phenomena but averaged waveforms typically do not even reflect the average amplitudes or latencies of the individual responses.
Injured, perturbed, or dysfunctional systems often show marked changes in fatigability, refractory periods, and supernormal periods after responses. For example, injured spinal cords show a greater tendency for fatigue after repeated stimuli, longer refractory periods, and the appearance of supernormal behavior at lower stimulus frequencies than normal spinal cords. Likewise, people with injured retinas or impaired hearing may show greater changes to rapidly repeated light flashes and sounds. The ability of the heart to respond to electrical pacing shows characteristics of fatigue, refractory period, and supernormality. Neural, muscular, cardiac, hormonal, vascular, and renal responses to repeated pharmacological manipulations can be quite different in different disease states and in the presence of certain drugs. Such behavioral changes of perturbed systems to repeated stimuli have important clinical implications and may also provide quantifiable and objective evidence of dysfunction in situations where conventional averaging approaches show little or inconsistent changes in averaged evoked responses.
Many excitable systems exhibit characteristic fluctuations in response amplitude and latencies with repeated stimuli. The fluctuations thus may be dynamical, i.e., have a chaotic rather than a random basis. Altered fluctuations may reflect the changing contributions of multiple and complex variables in the system. Averaging and parametric statistical analysis in conventional signal analysis typically assume that the signal fluctuations are due to noise and express the fluctuations as standard deviations or errors of mean. Quantification of the fluctuation and distinguishing between dynamical changes and noise therefore may provide insight into the nature and extent of the injury or system perturbation causing altered fluctuations. Such potentially important diagnostic and prognostic characteristics of responses are obscured by conventional averaging methods.
Conventional instruments designed for stimulating and analyzing responses in reactive systems thus suffer from several major deficiencies. Because the responses are often small relative to background, averaging is typically used to resolve the response, requiring repetitive stimulation of the systems. Averaging responses evoked by constant frequency stimulation, however, obscures certain behaviors of the responses to repeated stimuli. Response fatigue, refractory, and supernormal behaviors cannot be easily distinguished from each other or quantified. Due to signal-to-noise considerations, response thresholds are often difficult to estimate when stimulus intensities and consequently response amplitudes are low. While averaging responses to repeated stimuli eliminates response fluctuations and improves signal-to-noise ratios, much critical information is lost in the process. While parametric statistical analyses can be applied to measure the magnitude of response fluctuations during the stimulation, such analyses provide little insight into the causes of the fluctuations or the relationship of the fluctuations to change in the stimulus.
Accordingly, a new and different approach of stimulating and analyzing responses is needed to circumvent disadvantages of constant frequency stimulus methods and conventional averaging approaches to evoked responses. Such an approach should be able to detect, distinguish, and quantify fatigue, refractory, and supernormal behaviors without subjecting the system to prolonged high frequency stimulation. The approach should also be able to assess stimulus thresholds for low-level signals in high noise environments and to distinguish between noise and dynamical fluctuations of responses to repeated stimuli. Finally, the approach should be compatible with existing methodologies and preferably collect and provide the same information for comparison.